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AgentPay x402 — Economic-intelligence layer for AI Agents

fear_greed_index

Read-onlyIdempotent

Gauge overall crypto market sentiment with a 0-100 index, from extreme fear to extreme greed, plus optional daily history.

Instructions

Crypto Fear & Greed Index (0=extreme fear, 100=extreme greed) with optional history

Use when: You need to gauge overall crypto market sentiment or mood — whether the market is fearful or greedy. Not for: you want token-specific sentiment — crypto_news (per-token headlines) or funding_rates (leveraged positioning). Returns: value (0–100), value_classification (e.g. 'Greed'), optional history[] Example response: {"value": 10, "value_classification": "Extreme Fear", "timestamp": 1774137600, "source": "alternative.me"}

Price: free. Read-only live public data; no API key, nothing signed or spent. Fails with an error message on an unknown symbol or an unreachable upstream source.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of days of history to return (default 1, max 30)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so safety is covered structurally. The description adds genuinely useful context beyond that: free, no API key, nothing signed or spent, and error behavior on unreachable upstream. It loses a point because the advertised failure mode 'unknown symbol' is inconsistent with a schema that only exposes a limit parameter and accepts no symbol.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core purpose, then cleanly sectioned into Use when / Not for / Returns / Example / Cost. Every sentence carries distinct information; the labeled structure makes scanning fast.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so the description carries the return-value burden and does so explicitly: value, value_classification, optional history, plus a concrete example response. Combined with auth and failure-mode notes, an agent has everything needed to call and interpret it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There is a single optional parameter (limit) already fully documented in the schema at 100% coverage, including default and max. The description adds no syntax or semantics beyond that, so the baseline 3 for high schema coverage applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific resource (Crypto Fear & Greed Index) with its scale semantics (0=extreme fear, 100=extreme greed) and optional history. It explicitly distinguishes itself from token-specific siblings (crypto_news, funding_rates), so an agent can route correctly without opening schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides an explicit 'Use when' condition (gauge overall market sentiment) and a 'Not for' clause naming two concrete alternative tools for token-specific sentiment. This is the when/when-not/alternatives pattern at full strength.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.